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Modern CNNs for IoT Based Farms

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Information and Communication Technology for Development for Africa (ICT4DA 2019)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1026))

Abstract

Recent introduction of ICT in agriculture has brought a number of changes in the way farming is done. This means use of Internet of Things(IoT), Cloud Computing(CC), Big Data (BD) and automation to gain better control over the process of farming. As the use of these technologies in farms has grown exponentially with massive data production, there is need to develop and use state-of-the-art tools in order to gain more insight from the data within reasonable time. In this paper, we present an initial understanding of Convolutional Neural Network (CNN), the recent architectures of state-of-the-art CNN and their underlying complexities. Then we propose a classification taxonomy tailored for agricultural application of CNN. Finally, we present a comprehensive review of research dedicated to applications of state-of-the-art CNNs in agricultural production systems. Our contribution is in two-fold. First, for end users of agricultural deep learning tools, our benchmarking finding can serve as a guide to selecting appropriate architecture to use. Second, for agricultural software developers of deep learning tools, our in-depth analysis explains the state-of-the-art CNN complexities and points out possible future directions to further optimize the running performance.

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Author information

Authors and Affiliations

  1. Department of Information Technology, Dedan Kimathi University of Technology, Nyeri, Kenya

    Patrick Kinyua Gikunda

  2. Le Laboratoire d’Informatique Avancée de Saint-Denis (LIASD), University of Paris 8, Saint-Denis, France

    Patrick Kinyua Gikunda & Nicolas Jouandeau

Authors
  1. Patrick Kinyua Gikunda
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  2. Nicolas Jouandeau
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Correspondence to Patrick Kinyua Gikunda .

Editor information

Editors and Affiliations

  1. Council for Scientific and Industrial Research, Meraka ICT Institute, Pretoria, South Africa

    Fisseha Mekuria

  2. Department of Future Technologies, University of Turku, Turku, Finland

    Ethiopia Nigussie

  3. ICT4D Research Center, Bahir Dar University, Bahir Dar , Ethiopia

    Tesfa Tegegne

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Gikunda, P.K., Jouandeau, N. (2019). Modern CNNs for IoT Based Farms. In: Mekuria, F., Nigussie, E., Tegegne, T. (eds) Information and Communication Technology for Development for Africa. ICT4DA 2019. Communications in Computer and Information Science, vol 1026. Springer, Cham. https://doi.org/10.1007/978-3-030-26630-1_7

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  • DOI: https://doi.org/10.1007/978-3-030-26630-1_7

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-26629-5

  • Online ISBN: 978-3-030-26630-1

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